Triple
T26014313
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Muisca language |
E646982
|
entity |
| Predicate | lexicalDomain |
P29095
|
FINISHED |
| Object | rich agricultural vocabulary |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: rich agricultural vocabulary | Statement: [Muisca language, lexicalDomain, rich agricultural vocabulary]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lexicalDomain Context triple: [Muisca language, lexicalDomain, rich agricultural vocabulary]
-
A.
lexicalResources
Indicates that one entity provides or is associated with lexical materials (such as dictionaries, vocabularies, or word lists) that support or describe another entity.
-
B.
lexicalEvidence
Indicates that there is supporting information or justification for something based specifically on the form, structure, or usage of words in a language.
-
C.
termLanguage
Indicates the language in which a given term is expressed or defined.
-
D.
linguisticField
chosen
Indicates that something pertains to or is associated with a particular area or subdiscipline within linguistics.
-
E.
languageTerm
Indicates that one entity is a linguistic expression (word, phrase, or term) used to denote or label the other entity.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69e77e8aa65881909ca58918f29ab2a0 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f605b7eb6881909e1768f5f856be32 |
completed | May 2, 2026, 2:10 p.m. |
| PD | Predicate disambiguation | batch_69f4a10728e08190bc0b96c558740f51 |
completed | May 1, 2026, 12:48 p.m. |
Created at: April 22, 2026, 9:03 a.m.